System for automated determination of retroreflectivity of road signs and other reflective objects

ABSTRACT

A system for the automated determination of retroreflectivity values for reflective surfaces disposed along a roadway repeatedly illuminates an area along the roadway that includes at least one reflective surface using a strobing light source. Multiple light intensity values are measured over a field of view which includes at least a portion of the area illuminated by the light source. A computer processing system is used to identifying a portion of the light intensity values associated with a reflective surface and analyze the portion of the light intensity values to determine at least one retroreflectivity value for that reflective surface.

RELATED APPLICATIONS

This application is a continuation of application Ser. No. 11/381,503filed May 3, 2006, now U.S. Pat. No. 7,173,707 issued Feb. 3, 2007,which in turn is a continuation of application Ser. No. 10/736,454 filedDec. 15, 2003, now U.S. Pat. No. 7,043,057 issued May 9, 2006, which inturn is a continuation of Ser. No. 09/918,375 filed Jul. 30, 2001 nowU.S. Pat. No. 6,674,878 issued Jan. 6, 2004.

FIELD OF THE INVENTION

The present invention relates to the field of automated electronicmeasurement and object identification systems. More particularly, thepresent invention is directed to methods and an apparatus for theautomated determination of certain characteristics of desired reflectiveobjects (such as road signs) and classifying the reflective objects asto the level of retroreflectivity.

BACKGROUND OF THE INVENTION

Safe motor vehicle travel during low light and nighttime conditionsrequires that directional, regulatory and cautionary informationdisplayed upon road signs and markers be clearly visible to a vehicleoperator traveling at a reasonable velocity down a roadway. Variouskinds of reflective sheeting, decals and paints are used on road signsand markers to enhance the readability and perception of informationdisplayed during low light and nighttime conditions. Unfortunately, theeffectiveness of these reflective materials tends to deteriorate overtime.

Adequate nighttime and low light visibility of roadway signs by vehicleoperators is best associated and most impacted with the retroreflectanceproperties of the individual signs. Retroreflectivity (defined as theability of a material to reflect incident light back towards itssource), specified in candelas per lux per square meter (cd/lux/m²), isan important characteristic utilized by transportation agencies toassess the nighttime visibility of road signs.

Generally, highway and street maintenance departments do notsystematically evaluate the deterioration of the reflective materialsused on road signs and markers. If inspections of road signs or markersare performed, they are typically accomplished by having inspectorsmanually position a handheld retroreflectometer directly on the surfaceof a sign in order to determine a retroreflectivity value for that sign.When there are a large number of road signs or markers (sometimesreferred to as traffic control devices or TCDs) in a given jurisdiction,the task of manually inspecting all of these road signs and markers canbe time consuming and expensive.

One technique for determining retroreflectivity which does not requirethat a retroreflectometer be placed directly on a sign is described inU.S. Pat. No. 6,212,480 entitled, “APPARATUS AND METHOD FOR DETERMININGPRECISION REFLECTIVITY OF HIGHWAY SIGNS AND OTHER REFLECTIVE OBJECTSUTILIZING AN OPTICAL RANGE FINDER INSTRUMENT,” issued Apr. 3, 2001 toDunne. The Dunne patent relates to a device commercialized by theassignee thereof and marketed as the “Impulse RM” retroreflectometer byLaser Technology, Inc., of Englewood, Colo., USA. In use, handhelddevices fabricated according to the Dunne patent are manually directedtoward, or precisely at, a target object and then manually “fired.” Oncefired, the handheld device bounces a laser off the target object andmeasures the reflected laser energy that is then used to determine aretroreflectivity.

There are several drawbacks of the handheld laser arrangement describedby the Dunne patent. The handheld device can only measure a single colorat a time and can only measure one object at a time. The determinationof retroreflectivity for a given object is valid only for the actuallocation, or discrete measurement point, along the roadway at which themeasurement was made by the human operator. In order to validate ameasurement made by such devices, the device must be taken back to theprecise location in the field where an original measurement occurred fora valid comparison measurement to be made.

Another technique established for determining the nighttime visibilityof signs has been introduced by the Federal Highway Administration(FHWA). The Sign Management and Retroreflectivity Tracking System(SMARTS) is a vehicle that contains one high intensity flash source(similar to the Honeywell StrobeGuard™ SG-60 device), one color camera,two black and white cameras, and a range-sensing device. The SMARTSvehicle requires two people for proper operation—one driver and onesystem operator to point the device at the target sign and arm thesystem. The SMARTS travels down the road, and the system operator “lockson” to a sign up ahead by rotating the camera and light assembly topoint at the sign. At a distance of 60 meters, the system triggers theflash source to illuminate the sign surface, an image of which iscaptured by one of the black and white cameras. A histogram is producedof the sign's legend and background that is then used to calculateretroreflectivity. A GPS system stores the location of the vehicle alongwith the calculated retroreflectivity in a computer database.

Like the handheld laser device of the Dunne patent, the SMARTS devicecan only determine retroreflectivity for one sign at a time and can onlydetermine retroreflectivity for the discrete point on the roadway 60meters from the sign. Two people are required to operate the vehicle andmeasurement system. The SMARTS vehicle cannot make retroreflectivitydeterminations for signs on both sides of the roadway in a single passover the roadway and does not produce nighttime sign visibilityinformation for lanes on the roadway not traveled by the vehicle.Because the system operator in the SMARTS vehicle must locate and tracksigns to be measured while the vehicle is in motion, a high level ofoperational skill is required and the likelihood that a sign will bemissed is significant.

There are an estimated 58 million individual TCDs that must be monitoredand maintained in the United States and new TCD installations increasethis number daily. For the reasons that have been described, theexisting techniques for determining retroreflectivity do not lendthemselves to increasing processing throughput so as to more easilymanage the monitoring and maintenance of these TCDs. So called automateddata collection systems often require that normal traffic be stoppedduring data collection because either the acquisition vehicle moved veryslowly or because the acquisition vehicle had to come to a full stopbefore recording data about the roadside scene. Furthermore, a humanoperator is required to point one or more measurement devices at a signof interest, perform data collection for that particular sign and thenset up the device for another particular sign of interest. With such alarge number of TCDs that must be monitored, it would be desirable toprovide an automated system for determining the retroreflectivity ofroad signs and markers that addresses these and other shortcomings ofthe existing techniques to enable a higher processing throughput of anautomated determination of the retroreflectivity of road signs andmarkers.

SUMMARY OF THE INVENTION

The present invention provides a system for the automated determinationof retroreflectivity values for reflective surfaces disposed along aroadway. An area along the roadway that includes at least one reflectivesurface is repeatedly illuminated by a light source and multiple lightintensity values are measured over a field of view which includes atleast a portion of the area illuminated by the light source. A computerprocessing system is used to identify a portion of the light intensityvalues associated with a reflective surface and analyze the portion ofthe light intensity values to determine at least one retroreflectivityvalue for that reflective surface. Preferably, color images of the areaand locational information are also generated by the system and are usedtogether with a characterization profile of the light source to enhancethe accuracy of the determination of retroreflectivity values. In oneembodiment, a three-dimensional overlay of retroreflectivity values forthe roadway is generated and can be manipulated to displayretroreflectivity values of a reflective surface at any desired pointalong the roadway. In another embodiment, a virtual drive-through alonga roadway is simulated using a plurality of retroreflectivity values tosimulate reflections from each reflective surface disposed along theroadway during the virtual drive-through.

In contrast to the existing techniques for determining retroreflectivitythat require an operator to target individual signs from a knowndistance, the present invention can determine retroreflectivity withouttargeting individual signs and can calculate retroreflectivity values atany desired point along a roadway. To overcome the limitations imposedby the existing techniques, the present invention employs severalenhancements that are designed to improve the accuracy of evaluatingintensity measurements made over a view where the reflective surfacesare not individually targeted and, therefore, neither the distance tothe reflective surface or the normal vector to the reflective surfaceare known.

In a method in accordance with the present invention, retroreflectivityvalues for reflective surfaces disposed along a roadway are determinedin an automated manner. A light source is strobed as the light source istraversed along the roadway to illuminate an area that includes at leastone reflective surface. A plurality of light intensity measurements arecollected using at least one intensity sensor directed to cover a fieldof view which includes at least a portion of the area illuminated by thelight source. A computer processing system is then used to identify aportion of at least one light intensity measurement associated with oneof the at least one reflective surfaces and analyze the portion of theat least one light intensity measurement to determine at least oneretroreflectivity value for that reflective surface.

In a preferred embodiment of the method in accordance with the presentinvention, a characterization profile for the light source is createdfor this method. The characterization profile includes an array of knownluminance values of reflections of the light source. Thecharacterization profile for the light source is then utilized as partof determining the at least one retroreflectivity value for thatreflective surface. Preferably, the array of known luminance values ofreflection comprises reflected intensity values for the light sourceover a range of colors and reflected intensity values over a range ofrelative angles between the light source and the reflective surface. Inone embodiment, a plurality of color images are captured using at leastone color camera directed to cover a field of view which includes atleast a portion of the area illuminated by the light source. The rangeof colors of the characterization profile for the light source and theplurality of color images are then used as part of determining the atleast one retroreflectivity value for that reflective surface. Inanother embodiment, locational information is obtained for each of theplurality of light intensity measurements and used to determine acoordinate location for each reflective surface. The range of relativeangles of the characterization profile for the light source and thecoordinate location are then used as part of determining the at leastone retroreflectivity value for that reflective surface. Preferably, acharacterization profile of the light intensity sensor is also utilizedto further enhance the accuracy of the system. The characterizationprofile for the intensity sensor preferably includes an array ofintensity values of reflections as measured by the intensity sensor inresponse to a known light source.

A system for acquiring information to assess reflective surfacesdisposed along a roadway in accordance with the present inventionincludes a vehicle and a computer processing system. The vehicleincludes at least one high output light source, at least one intensitysensor, at least one color camera, a positioning system, and a controlsystem. The control system is operably connected to the light source,intensity sensor, color camera and positioning system such that theintensity sensor, color camera and positioning system record informationassociated with an area that includes at least one reflective surface asthe vehicle traverses along the roadway in response to repeatedillumination of the area by the light source. The computer processor,which may reside within the vehicle or may be located separate from thevehicle, utilizes the recorded information to determine at least oneretroreflectivity value for the at least one reflective surface.

In a preferred embodiment of the system, the vehicle further includes alaser scanning system that records distance information including atleast a distance between the vehicle and each of the at least onereflective surfaces. The computer processing system utilizes thedistance information generated by the laser scanning system to determineat least a normal vector for a face of the reflective surface.Preferably, the high output light source comprises at least two strobelights arranged to alternatively illuminate the area at an effectivestrobe rate of at least one flash per second. Preferably, the intensitysensor comprises a black and white camera and the color camera comprisesa pair of digital color cameras mounted on the vehicle to generatestereoscopic images of the area. The positioning system is preferably aglobal positioning system supplemented with an inertial navigationsystem. In the embodiment in which at least a portion of the computerprocessing system resides within the acquisition vehicle, at least aportion of the control system is preferably implemented using thecomputer processing system and a master clock supplied to all of theremaining components of the system to synchronize the system.

In another embodiment of the present invention, a method for displayingand manipulating retroreflectivity data for a reflective surfacedisposed along a roadway is provided. A plurality of retroreflectivityvalues for the reflective surface are determined, preferably using themethod and system as described. A three-dimensional representation ofretroreflectivity values of the reflective surface is generated and thethree-dimensional representation of retroreflectivity values isdisplayed, preferably as an overlay over a depiction of a roadway. Asimulation of the interaction of a vehicle operator/observer isaccomplished by generating a simulated vehicle light source and avehicle operator/observer pair and, for different locations of thesimulated vehicle light source and said vehicle operator/observer pair,generating a simulated vehicle operator/observer observation angle and asimulated view of the vehicle pathway which includes the reflectivesurface. The simulation allows for simulating a changing magnitude ofambient lighting from a first value to a second value, or simulating achange of at least one characteristic of the depiction of the roadway. Acorresponding change in the three-dimensional representation ofretroreflectivity values as a result is determined and also simulated onthe display. In one embodiment, the simulation is used to generate a newthree-dimensional depiction of the reflective surface according to apredictive aging model which includes a gradual degradation of thereflective surface over time. The reflective surface can then berepresented and simulated as if the reflective surface exhibited such agradual degradation in the three-dimensional depiction.

In another embodiment, a method for simulating a virtual drive-throughof a roadway that includes at least one reflective surface disposedalong the roadway is provided. A plurality of retroreflectivity valuesare determined for each reflective surface. A virtual drive-throughalong the roadway is simulated using the plurality of retroreflectivityvalues to simulate reflections from each reflective surface disposedalong the roadway during the virtual drive-through. Preferably, thevirtual drive through allows for a simulation of a change of at leastone characteristic of the depiction of the roadway, such that acorresponding change in the reflections from each reflective surface isdetermined and simulated. Preferably, the virtual drive-throughsimulates at least one vehicle having a light source and observer pair.In this embodiment, the virtual drive-through allows for a simulation ofa change of at least one characteristic of the vehicle or light sourceand observer pair, such that a corresponding change in the reflectionsfrom each reflective surface is determined and simulated.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts the concept of observation angle (i.e., angle betweenincident light from a light source and an human observer [or lightsensor], of the light as reflected from the face of a reflective asset)in the context of a conventional passenger vehicle traversing a vehiclepathway and where light from the vehicle reflects from a stop sign tothe vehicle operator (shown in ghost).

FIG. 2 depicts the concept of entrance angle (i.e., angle betweenincident light from a light source mounted to a vehicle and a normalvector relative to the substantially flat face of a reflective surfacedisposed adjacent a vehicle pathway).

FIG. 3 depicts a block diagram of the systems, subsystems and processesfor capturing and processing roadside information from a moving platformin order to compute retroreflectivity according to the teaching of thepresent invention wherein the arrows connecting the blocks of thediagram illustrate the connections between the systems and subsystemsfor computing R_(A) for each reflective asset recorded by the system ofthe present invention.

FIG. 4 depicts in diagram form, a preferred configuration of a sensorsuite for use with a four-wheeled vehicle and the interconnections andcouplings between the physical subcomponents of a system designedaccording to the present invention.

FIG. 5 is a plan view of a divided multi-lane vehicle pathway anddepicts how periodic light intensity measurements may be made as avehicle traverses the vehicle pathway over time and the discretelocations where such periodic light intensity measurements are performedby a data acquisition vehicle operating in accordance with the presentinvention.

FIG. 6 depicts four digital frames of data as captured by the intensitysensor at various discrete locations along the vehicle pathway depictedin FIG. 5.

FIG. 7 depicts a flowchart showing the steps required to convertintensity measurements into foreground and background retroreflectivityfor a single reflective asset.

FIG. 8 depicts a typical light source intensity profile over the visibleelectromagnetic spectrum, which illustrates how different wavelengths ofelectromagnetic radiation possess different light intensities.

FIG. 9 depicts a preferred methodology for creating a three-dimensionalretroreflectivity profile for all lanes and locations adjacent a vehiclepathway for a single reflective asset or sign which three-dimensionalretroreflectivity profile is based upon a single pass of a dataacquisition vehicle over the vehicle pathway.

FIG. 10 illustrates the facts that the normal vector of a reflectiveasset and the sheeting type of such a reflective asset create symmetrythat may be used to determine retroreflectivity values along all rays(or vectors) that have the same relative angle to the normal vector ofthe reflective asset.

FIG. 11 depicts a typical map of roadway edges and lane dividers createdfrom the imaging system on-board the moving platform or data acquisitionvehicle.

FIG. 12 is an elevational side view depicting a three-dimensionalretroreflectivity profile for a stop sign created from the movingplatform wherein the height of the three-dimensional surface at eachpoint represents the magnitude of the retroreflectivity of the sign atthat point.

FIG. 13 is an elevational side view depicting a modifiedthree-dimensional retroreflectivity profile resulting from a change tothe sign sheeting type that produces higher intensity visible radiationreflected from the stop sign.

FIG. 14 is an elevational view depicting a modified three-dimensionalretroreflectivity profile resulting from a change in the angle of agiven reflective asset with respect to the roadway.

FIG. 15 depicts the modified three-dimensional retroreflectivity profileresulting from a change in the observation angle.

FIG. 16 depicts the geometry of entrance angle and observation angle forretroreflective pavement markings disposed upon a vehicle pathway.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Retroreflectivity, designated as “R_(A)” generally (and from time totime in this disclosure), varies according to two key parameters:observation angle and entrance angle. Observation angle 100 (See FIG. 1)is the angular displacement between a light source 110 and a lightsensor 120, as measured from an object face surface 130. In the case ofa vehicle 140 driven by vehicle operator 145 moving along a highway 150,observation angle 100 is defined by the distance of the vehicle 140 froma sign face surface 130, the placement of the light source (headlights)110 on the vehicle 140, and the position of the light sensor (eyes ofthe vehicle operator) 120 of the vehicle 140.

Entrance angle 160 (See FIG. 2) is defined as the angular displacementof the incident light 170 relative to the normal vector 180 from theobject face surface 130. Entrance angles are impacted by the angularposition 200 of a sign 190 relative to the highway 150, the sign 190lateral distance 210 from the highway 150, and the distance 220 of thevehicle 140 from the sign 190. The inventors hereof are believed to bethe first persons to successfully decrease the complexity and increasethe efficiency of determination of R_(A) in the field.

The method of automatic determination of R_(A) (See FIGS. 3 and 4)preferably utilizes a plurality of subsystems located on/in a capturevehicle 225. These subsystems include a light intensity measurementsystem 230, a vehicle positioning system 240, a color image capturesystem 250 and a data recording system 260. The light intensitymeasurement system 230 preferably includes a high output light source270, a light intensity sensor 280 and an intensity measurement systemcontrol 290. A plurality of intensity measurements 300 are generated bythe intensity measurement system 230 in response to the repeatedstrobing of the high output light source 270. The vehicle positioningsystem 240 preferably includes a GPS receiver 310, an inertialnavigation system 320, a distance measuring instrument 330 and a masterclock 340. A position measurement 350 is generated by the vehiclepositioning system 240. The color image capture system 250 preferablyincludes a stereoscopic camera pair 360, iris controls 370 and imagecapture control 380. The image capture system 250 generates a digitalimagery stream 390.

The data required for the automated determination of R_(A) isaccumulated while traversing a highway 150 with the capture vehicle 225(See FIGS. 5 and 6). The capture vehicle 225 is shown on a 4-lanedivided highway 400 with the capture vehicle 225 located in a proximatelane 410 to the stop sign 190. Preferably, a series of reflected lightintensity frames 420 are generated at a constant measurement interval430 as the capture vehicle travels along the highway 150.

Characterization of sign 190 R_(A) preferably utilizes the datarecording system 260 to create a single tagged video stream 440 from thereflected light intensity frames 420, position measurements 350 anddigital imagery 390 for each capture event 430 (See FIGS. 3, 5, 6, 7 and8). A computer processor 450 identifies an object of interest 460 in aportion of the intensity frame 420 and determines the object of interestattributes 465 associated with that object of interest. Preferably, theobject of interests are identified from the digital imagery stream 390generated by the color image capture system 250 in the manner as taughtby U.S. Pat. No. 6,266,442. Alternatively, other techniques known in theart for isolating an object of interest in a videostream can be used.Preferably, the computer processor 450 correlates the portion of animage frame of the digital imagery stream 290 with a similar portion ofthe intensity frame 420 containing the object of interest 460.

For each object of interest 460, a background intensity measurement 470and a foreground intensity measurement 480 is generated. Using anintensity algorithm 490, a light intensity sensor characterization 275and a look-up-table 475, the computer processor 450 determines abackground luminance value 500 and a foreground luminance value 510.Based on the background luminance value 500, the foreground luminancevalue 510, a characterization of light source wavelength 540, thebackground sheeting color 505 and the foreground sheeting color 506 thecomputer processor 450 characterizes a background R_(A) 520 and aforeground R_(A) 530 which are preferably reported separately for thatobject of interest.

The automated determination of multiple R_(A) values for a given objectof interest 460 allows for the extrapolation of R_(A) values at anunmeasured viewing point 550 for an object of interest, such as a sign190 (See FIGS. 9 and 10). In this example, the unmeasured viewing pointresides in a nontraversed lane 560. The computer processor 450 definesan undetermined retroreflectivity ray 570 for unmeasured viewing point550. Using interpolated values, the computer processor 450 determines anR_(A) value for unmeasured viewing point 550 and any point located alongundetermined retroreflectivity ray 570.

In one embodiment, the computer processor 450 can generate a simulatedroadway 580 including roadway edges 585 and lane dividers 586 frominformation captured by the color imaging system 250 (See FIGS. 11, 12,13, 14 and 15). The computer processor 450 then generates athree-dimensional sign R_(A) profile 590 for either foreground R_(A) 530or background R_(A) 520 to be overlayed on the simulated roadway 580.The computer processor 450, or any other computer processor accessing ina standalone end user mode accessing the retroreflectivity data, canmanipulate the data such that additional simulations can be performedincluding a sheeting type improvement simulation 600, a sign profilerotation simulation 610 and a observation angle simulation 620.

An alternative embodiment of the present invention allows for thedetermination of retroreflectivity for pavement markings 630 (See FIG.16). While the reflective surfaces of the present invention aredescribed with respect to road signs and pavement markings along aroadway, it will be understood that the present invention is equallyapplicable to other reflective surfaces such as taillights or vehiclemarkings and to environments other than roadways such as airportrunways, factories or the like.

Pursuant to the teaching of the present invention, a method andapparatus for determining retroreflectivity of relatively flat surfaceportions of objects disposed adjacent a highway 150 traversed by avehicle 140 are taught, enabled and depicted. The present invention maybe utilized to detect and determine a retroreflective surface ofinterest disposed in a scene of non-retroreflective surfaces. That is,at least one object face surface 130 which exhibits retroreflectivityover at least a relatively narrow conical volume of magnitude of severaldegrees from a normal vector 180 originating from said object facesurface 130.

In accordance with the present invention, a determination of theretroreflectivity of objects adjacent a highway 150 preferably includes(i) providing position measurements 350 of a capture vehicle 225; (ii)precise position of the object of interest 460, or sign 190; (iii)intensity measurements 300 from a high output light source 270 and lightintensity sensor 280 at measurement intervals 430 along said highway150. Thus, a single-pass along the highway 150 by the capture vehicle225 operating the light intensity measurement system 230, vehiclepositioning system 240, image capture system 250 and data recordingsystem 260 taught herein eliminates many shortcomings of the prior artand allows a single vehicle operator to conduct virtually continuousdata measurement and acquisition of objects of interest 460 disposedadjacent a highway 150, at capture events 430 on said highway 150,without disrupting or interrupting other vehicle traffic traversing saidhighway 150.

FIG. 3 shows a block diagram of the on-board systems and the desktopsystems required to record a tagged videostream 440 and createthree-dimensional (3D) sign R_(A) profiles 590 for various signs 190along a highway 150. The vehicle positioning system 240 contains all ofthe equipment to precisely locate the capture vehicle 225. All locationinformation is synchronized with a master clock 340, preferablyassociated with a computer processor 450, which allows other data typesto be merged with the vehicle location information at later stages inthe post-processing. All of the on-board systems utilize the same masterclock 340 information, thus allowing any events (image capture system250, intensity measurement 300, and trigger controls 227, 228) to becorrelated to the precise vehicle location and attitude duringreal-time, near real-time, or post-processing of the data acquired bythe capture vehicle 225.

The image capture system 250 consists of at least one set ofstereoscopic cameras 360 that gather digital imagery along the highway150. Each capture event is combined with time stamp information from thevehicle positioning system 240 which also provides trigger control 227for the image capture system 250 and trigger control 228 for the lightintensity measurement system 230. These images and associated timestamps are later combined with photogrammetry to create objects ofinterest 460 and their associated attributes 465.

The light intensity measurement system 230 preferably consists of atleast one high output light source(s) 270 and the associated lightintensity sensor(s) 280. The precise control for these items iscontained within the light intensity measurement system 230, and mastertime sequencing instrument 340 information received from the vehiclepositioning system 240 (or computer processor 450) is combined to createa tagged videostream 440 so precise vehicle information can be utilizedduring post-processing.

The data recording system 260 is constantly monitoring controlinformation from the other three on-board systems and records thenecessary information. No post-processing is performed in the datarecording system 260. As computer power increases in the future, oneskilled in the art could produce a system whereby most, if not all, ofthe post-processing functions were performed in the capture vehicle 225,perhaps even in real-time. The inventors can imagine several uses forthe production of real-time information from the image capture system250 in the future, but the cost of obtaining such information withtoday's computing power makes this option prohibitively expensive today.

The lower half of FIG. 3 shows the functional blocks for datapost-processing. There are two main functions—the creation of objects ofinterest 460 and their associated attributes 465, and the determinationof retroreflectivity for each object of interest 460. There are manymethods for creating objects of interest 460 from digital imagery, a fewof which are discussed in this disclosure. The specific steps requiredto compute R_(A) are outlined in the discussion below.

FIG. 4 shows a typical configuration within a capture vehicle that iscapable of producing data and imagery to create digital representationsof objects of interest 460 and objects of interest retroreflectivity466. The distance measuring instrument (DMI) 330, GPS receiver 310 andinertial navigation system (INS) 320 constitute the vehicle positioningsystem 240. Not all of these components are necessary to obtain thedesired results, but better precision, and therefore more meaningfuldata, are produced if all three components are included.

The high output light source(s) 270 and light intensity sensor(s) 280constitute the light intensity measurement system 230. These componentsmake it possible to gather on-the-fly information for a desired highway150 to allow the computation of object of interest retroreflectivity466, as well as create a full three-dimensional sign R_(A) profile 590for those same objects of interest 460.

The stereoscopic cameras 360 constitute the digital imagery system 390that allows for the creation of objects of interest 460 and theirassociated attributes 465 during post-processing. More than one set ofstereoscopic cameras 360 can be employed, thus increasing the accuracyof positional measurements for objects of interest 460. Other,non-stereoscopic imaging systems could also be employed with little orno change to the vehicle positioning system 240 or to the lightintensity measurement system 230.

FIG. 5 shows the top view of a four-lane divided highway 400 with a stopsign 190. The capture vehicle 225 is traveling in the proximate lane 410to the stop sign 190 and makes intensity measurements 300 at captureevents 430 while traveling the depicted route. The techniques describedherein will allow a retroreflectivity value for this stop sign 190 to becomputed for any point along the 4-lane divided highway 400, independentof whether the intensity measurement 300 was made at that point, andalso independent of whether the capture vehicle 225 actually drove overthat point.

It should be noted that intensity measurements 300 are made continuouslywhile the capture vehicle 225 is in motion, thus requiring no priorknowledge of either the positions or the existence of signs.

FIG. 6 shows some typical reflected light intensity frames 420 ascaptured by the light intensity sensor 280 at various discrete locationsalong the roadway. These reflected light intensity frames 420 are theresult of the high output light source 270 being energized (or flashed)while each reflected light intensity frame 420 is captured by one ormore light intensity sensors 280. Since most of the objects in the sceneare not reflective, and due to the high setting of the threshold rangein the light intensity sensor(s) 280, the reflected light intensityframes 420 will actually show very few objects. For effective luminanceresults throughout a wide range of retroreflective materials, more thanone light intensity sensor 280 may be required in order to get enoughlevels of gray within the active part of the visible spectrum. Whenmultiple light intensity sensors 280 are required or used, they may eachhave different threshold ranges and each, thus, detect luminance valuesin different parts of the desired luminance ranges.

In order to compute retroreflectivity (R_(A)), one needs to know theluminance of the reflected energy. Luminance (expressed in candelas persquare meter, or cd/m²) will vary according to the intensity sensorcharacterization profile 275 of the light intensity sensor(s) 280 andthe color of the material from which light is reflected.

Most roadway signs 190 contain text and/or symbols overlaid on abackground. To ensure maximum visibility during day and nightconditions, the colors of the foreground information (text and/orsymbols) are chosen to have maximum day and night contrast with thebackground material. The techniques taught herein allow theretroreflectivity of roadway signs 190 to be determined for bothforeground and background materials. Computing both the foreground 530and background retroreflectivity 520 for each object of interest 460allows us to ensure that the proper nighttime contrast is achieved forroadside assets. For example, a stop sign 190 with a red background andwhite lettering can provide good daytime contrast between the text andthe sign background. But if these two materials display very similarretroreflectivity characteristics, their nighttime contrast will beminimal, thus rendering the sign ineffective during nighttimeconditions.

FIG. 7 shows a block diagram of the steps required to transformintensity measurements 300 into foreground luminance values 510 andbackground luminance values 500. First, a black and white camera ispreferably used as a light intensity sensor 280 to maximize thesensitivity of intensity measurements 300 (intensity will be determinedfrom the gray value of the corresponding pixels). Think of an intensitymeasurement 300 as intensity values for N discrete points within thescene, where N corresponds to the number of pixels in the lightintensity sensor's 280 array. For a light intensity sensor 280 that hasa resolution of 640×480 pixels, there are 307,200 discrete intensityvalues for each intensity sensor measurement 300. Although the preferredembodiment utilizes an intensity sensor measurement 300 in the form ofan array of discrete pixel intensity values, preferably a single pixelintensity value is selected and utilized for the automated determinationof a corresponding retroreflectivity value. Alternatively, an average orother combination of a group of pixel intensity values could be utilizedfor the automated determination of a corresponding retroreflectivityvalue. Intensity values will vary according to the color of thereflected light, since not all colors of incoming light excite the lightintensity sensor 280 pixels in the same way. By knowing the backgroundor foreground color of the object of interest 460 along with the lightintensity sensor's 280 ability to sense, or the light intensity sensor's280 profile for a particular color, the intensity value 300 for aparticular color can be converted into a luminance value. Lightintensity sensor 280 characterization is essential for high precisioncomputations since N photons of a given particular color (or wavelength)of light will represent a different gray value (intensity level) in thesensor than N photons of another color (or wavelength) of light. Thelook-up-table (LUT) 475 shown in FIG. 7 is a digital table stored inmemory that uses the indexes of intensity (a single gray level valuefrom the intensity measurement 300) and sheeting color to determine theluminance. The light intensity sensor characterization 275 is empiricalinformation about the light intensity sensor 280 that is used to createthe LUT 475. The same LUT 475 is used for computing foreground 510 andbackground luminance values 500.

The reader should note and appreciate that luminance is strictly ameasure of the reflected light, while retroreflectivity (or R_(A),expressed in candelas/lux/m²) is a measure of the reflected light withrespect to the incident light for that object. FIG. 7 shows theinformation needed to accurately convert luminance to R_(A): sensorlocation, object location, light source characterization, and color ofreflective material. For less precise R_(A) computations, a subset ofthe aforementioned characteristics can be utilized. For example, if auniform light source (equal intensity throughout the scene), columnatedlight reflected from the surface of the object of interest 460, and aknown distance 220 between the object of interest 460 and the lightintensity sensor 280 are all assumed, then the sheeting color andluminance value may be used to determine a rough approximation (within20%, for example) for R_(A).

To obtain the highest quality R_(A) calculations, all of the data shownin FIG. 7 should be utilized. The characterization of light source angledefines the amount of light emitted from the high output light source270 throughout the source's field of view. Due to the limitations oflamp design and their associated reflectors, most semi-uniform lightsources will have their greatest intensity at or near the normal vectorfor the light source. Since the high output light source(s) 270 are notaimed at objects of interest 460, the part of the incident light beamthat is striking the object of interest 460 when the intensitymeasurement 300 is captured must be determined. Light source anglecharacterization is a process whereby empirical data from the light ismodeled to establish the light intensity for numerous discrete vectorsfrom the center of the light. When intensity values are determined for adiscrete point in the scene (from the object's face surface 130), thelight intensity sensor 280 location and heading, as well as the objectof interest 460 location, are used to determine which light vectoreliminating from the light source was responsible for the resultingintensity measurement. The characterization of light source angletherefore, is a look-up-table where an object of interest's 460 angulardisplacement from the normal vector 180 for the high output light source270 is converted to a light intensity for the associated vector.

Since the beam from the high output light source 270 is diverging,objects of interest 460 farther from the origin of the light willreceive less incident radiation than those objects of interest 460closer to the light. The characterization of light source angle isconstructed at a few discrete distances from the light. Simple geometrycan be used to compute the incident radiation (using an interpolationmethod for an actual distance between two discrete distances in thecharacterization of light source angle) hitting the actual object ofinterest 460 based on the empirical data from the characterization oflight source angle.

The preferred high output light source 270 is a uniform full-spectrum(visible spectrum) light. In practice, this light source will not emitthe same intensity for all wavelengths of visible light. One variable oflight source color characterization that should be considered is theoutput profile of the light throughout the visible spectrum. FIG. 8shows a typical full-spectrum light source output profile. Note that theintensity in the blue area (400-500 nm) of the spectrum is stronger thanin the red area (600-700 nm). This profile specifies the amount of lightenergy (number of photons) emitted for a given frequency. Since R_(A)depends on the intensity of the incident light, the light source colorcharacterization 540, light source angle characterization 535,background sheeting color 505 and foreground sheeting color 506 must becombined to determine how the background luminance value 500 andforeground luminance value 510 is converted to R_(A) (i.e., what percentof the incident photons of the foreground/background color werereflected back to the sensor).

The divergence pattern for the light source may have different profilesfor various portions of the visible spectrum. In practice, a separatelight source angle characterization profile may be required for eachpossible foreground and background color of any given object of interest460.

A preferred high output light source 270 is of the type set forth in theattached installation and operation guide entitled “StrobeGuard™ HighIntensity Obstruction Lighting System, Model No. SG-60,” manufactured byHoneywell, Inc. In order to create a useful three-dimensional sign R_(A)profile 590 for an object of interest 460, intensity measurements 300for frequent capture events 430 along a highway 150 while the capturevehicle 225 is in motion. For example, at vehicle speeds of 50 miles perhour, intensity measurements 300 should be taken at a rate of at leasttwo per second. The StrobeGuard™ SG-60 model has a recharge time ofabout 1.5 seconds between successive flash events. As a result, oneSG-60 light will not provide enough flash events per second to allow anadequate number of intensity measurements 300. In order to meet therequirements of two flash events per second for a capture vehicle 225traveling at 50 miles per hour, three of the StrobeGuard™ SG-60 unitswould need to be fired in a synchronized, round-robin pattern to obtainenough trigger events.

The light intensity measurement system 230 described herein attempts toremove observation angle 100 as an R_(A) variable. This is done bykeeping the offset between the high output light source(s) 270 and lightintensity sensor(s) 280 as low as possible. Once a simulated roadway 580is created, observation angles 100 can be varied within thethree-dimensional display software or within the virtual drive-throughsoftware to show their effects on the R_(A) for the simulated roadway580 and any as-placed sign 190.

As mentioned previously, a R_(A) map of a simulated roadway 580 can becomputed, even though the intensity was not measured at every point andeven though the capture vehicle 225 did not drive over every point.First, it is critical that the geometry of R_(A) is understood.Reflective materials like sign sheeting are designed to projectnear-columnated light back toward the light source. If a perfectlycolumnated light being reflected from the object of interest 460 beingmeasured and a zero observation angle are assumed, the R_(A) values forall discrete locations along a ray projected from the object will beidentical.

FIG. 9 shows how to compute R_(A) for any discrete location along a4-lane divided highway 400. The R_(A) value for the desired point willbe based on the R_(A) value that lies along the pathway traveled by thedata acquisition vehicle 225. To compute this “reference R_(A) value”(the R_(A) value for a discrete location on or along a vehicle path), anundetermined retroreflectivity ray 570 is drawn from the desiredlocation to the face of the reflective asset. The discrete locationwhere the undetermined retroreflectivity ray 570 intersects the vehiclepath will be used as the reference R_(A) value. Since the discretelocation on the vehicle path will always lie between two measuredlocations where intensity measurements 300 were made, the referenceR_(A) value is computed by interpolating the two closest (in distance)R_(A) values along the vehicle path. As used herein, interpolate has theusual and typical meaning. It will be understood that interpolationconsistent with the present invention can involve interpolation followedby extrapolation and shall also include such other special mathematicalexpressions used or created to account for border effects and effects atthe lateral periphery and at the furthest distance where R_(A) may bereliably determined by application of the teaching of this disclosure.

If a perfectly columnated light is assumed, the value of R_(A) at thedesired point will be the same as the reference R_(A) value. Inpractice, all sign 190 sheeting materials will have some beam divergencefor reflected light. This beam divergence information can be used toadjust the computed R_(A) value up (or down) from the reference R_(A)value for discrete locations closer to (or farther from) the object'sface surface 130.

While knowing the normal vector 180 to a sign 190 face is not required,there are some advantages for planning and maintenance purposes thatmake the information useful. Several ways to compute the normal vector180 for a sign 190 exist. First of all, the “assumption” method requiresthat the normal vector 180 from the surface of the sign 190 is assumedto be parallel to the capture vehicle pathway 410 at the nearestlocation of the capture vehicle pathway 410 to the sign 190. Second, ascanning laser operating in conjunction with an optical sensor andhaving a common field of view may be used to more precisely resolve thenormal vector 180 from the object's face surface 130. Third,stereoscopic cameras 360 may be employed in a useful, albeit veryimprecise, manner of determining the normal vector 180. Fourth, theassumption method and stereo imaging method may be combined whereby thenormal vector 180 is assumed to lie parallel to the vehicle pathway 410unless the stereo imaging output renders the assumption false.

Of the methods listed above, the highest precision measuring systems fordetermining the normal vector 180 consists of a scanned laser andassociated optical sensor. This combination yields relative distancemeasurements between the capture vehicle 225 and the object's facesurface 130 that are more precise than optical measurements withcameras. A laser scanner attached to the capture vehicle 225 anddirected toward a roadside scene populated with retroreflective signs130 generates a series of reflection points to the optical sensor thatappear as a horizontal segment of points. The optical sensor must befast enough (i.e., have adequate data acquisition rates) to capture atleast several individual discrete measurements across the object's facesurface 130 (or of any other reflective asset). In general, two types oflaser scanners are suitable to be utilized according to the presentinvention; namely, single-axis scanners and dual-axis scanners. Apreferred sensor is of the type set forth in the proposal entitled,“Holometrics 3D Vision Technology,” as referenced in the previouslyidentified provisional patent application.

Since most all types of roadside signs 190 to be measured are disposedat various elevations relative to the highway 150 and the capturevehicle 225, a single-axis laser scanner cannot be mounted such that thescanning laser beam covers only a single elevation or constant heightrelative to the highway 150 and the capture vehicle 225. Rather, theinventors hereof suggest that use of a single-axis type laser scannermust either be mounted high on the capture vehicle 225 with a downwardfacing trajectory, or be mounted low on the capture vehicle 225 with anupward facing scanning trajectory. These two mounting schemes for asingle-axis laser scanner help ensure the lateral scan will intersectwith virtually every object face surface 130 of all signs 190 or otherobjects of interest 460 present in a roadside scene regardless of theelevation or height or such signs relative to the roadway or to themoving platform.

Dual-axis laser scanners 335 circumvent the varying sign height probleminherently encountered if a single-axis laser scanner is employed as thesource of integrated energy when practicing the teaching of the presentinvention. A dual-axis laser scanner 335 operates by continuously movingthe scanning beam scan up and down at a relatively slow rate whilesweeping the laser beam laterally from side to side across the field ofview at a relatively more rapid rate.

In order to obtain the normal vector 180 for a sign 190 as taughthereunder, only a select horizontal series of discrete locations acrossthe object's face surface 130 needs to be sensed by the high-speedoptical sensor. For each point in the horizontal series of discretelocations recorded for a given sign 190 due to the incident radiationprovided by the scanning laser, as sensed by the high speed opticalsensor, the precise direction of the incident laser is recorded, thusallowing both distance and direction of the measured point to bedetermined.

Either of the scanning methods produces a massive number of senseddiscrete locations representing discrete reflections of the incidentlaser radiation and each must be processed in order to correlate each ofthe sensed discrete locations with the object's face surface 130. Oncethe lateral series of discrete locations for a sign 190 is determined,simple triangulation methods are used to combine: (i) the vehiclelocation, (ii) vehicle heading vector, and (iii) scanned sign point toultimately determine the normal vector 180 for the object's face surface130.

As stated earlier, knowing the sign's 190 normal vector 180 can expandthe utilization of the present invention. The retroreflective propertiesof sign 190 sheeting materials are typically symmetrical about thevertical axis of the object's face surface 130. Because of thissymmetry, R_(A) values (either computed or extrapolated/interpolatedvalues) will be identical for rays that are symmetrical about thevertical axis.

FIG. 10 shows how the sign's 190 normal vector 180 can be used toextrapolate more R_(A) points. The R_(A) value for Point B is the sameas the R_(A) value for Point A since their angle relative to the normalvector 180 is the same and since their distance from the sign 190 is thesame. If Point B has the same relative angle (from the sign's 190 normalvector 180) as Point A, but lies closer to (or farther from) theobject's face surface 130, the sign 190 material's beam divergenceprofile can be used to adjust the R_(A) value for Point B up (or down)from the value obtained for Point A.

While the image capture system 250 described herein can be used forlocating objects of interest 460, it can also be used for mappingpurposes. By creating representations of roadway edges and lanedividers, a very precise map can be created from the same digitalimagery used for object of interest 460 creation. This mapping featureof the image capture system 250 will be a key component in thethree-dimensional sign R_(A) profile 590 mapping for signs and thevirtual drive through, both to be discussed later.

The image capture system 250 and light intensity measurement system 230are preferably free running, with measurements being made periodicallyduring capture vehicle 225 operation. There is no requirement that thesetwo systems be synchronized. In fact, these systems could operate incompletely different capture vehicles 225, if necessary. When bothsystems are contained within the same capture vehicle 225, the onlyconstraint for simultaneous operation is placed on the image capturesystem 250. Because of the intensity of the high output light source 270in the light intensity measurement system 230, it is preferred that theimage capture system 250 not capture frames at the same instant that thehigh output light source 270 is triggered. If images are actuallycaptured while the high output light source 270 is triggered, theirpositional results would still be valid, but the colors displayed wouldbe inaccurate because of the high output light being directed toward the(typically lower-thresholded) stereoscopic cameras 360.

One skilled in the art could completely eliminate any need for the imagecapture system 250 to know the firing events of the light intensitymeasurement system 230 by choosing sampling rates for the two systemsthat do not share any harmonic frequencies. On the rare occasions whenthe image capture system 250 captures images while the high output lightsource 270 is energized (or flashed), the skilled implementer could usetime stamps to determine when this system simultaneity occurred anddiscard the imaging frames.

Producing a simulated roadway 580 map is an essential part of creating athree-dimensional sign R_(A) profile 590 for a given vehicle 140pathway. All maps of a highway 150 will contain some degree of error.Even survey-grade maps, which are expensive to create and cumbersome tobuild, may have errors of a few centimeters to a few inches or more.Maps created via other methods, such as those made from data gatheredfrom capture vehicles 225, could have errors ranging from a fewcentimeters to several meters.

In practice, the simulated roadway 580 map created from the inventiveimage capture system 250 as disposed in or on a capture vehicle 225 andas otherwise described herein will be of higher value for thethree-dimensional sign R_(A) profile 590 than a survey-grade map. Eventhough the absolute errors may be greater in a two-dimensional orthree-dimensional map created using the image capture system 250 of thepresent invention, they will be very small relative to the actuallocation of individual objects of interest 460 and also very small withrespect to the discrete locations where the R_(A) measurements—bothcomputed and extrapolated or interpolated values—were made. The samesystematic location errors may permeate all data points, but therelative accuracy will be high. Since R_(A) is very dependent on thegeometry of the objects of interest 460 and the magnitude and directionof the light incident thereon, a high degree of relative accuracy ismore important than high absolute accuracy in creating a simulatedroadway 580 base map of such all inventoried objects of interest 460.

FIG. 11 shows another typical highway 150 that was driven by a capturevehicle 225 fabricated according to the teaching of the presentinvention. Data from this capture vehicle's 225 image capture system 250was used to create the simulated roadway 580 map including roadway edges585 and lane dividers 586. The same image capture system 250 data wasused to locate the sign 190, measure its size, and determine otherattributes. This same capture vehicle 225 also gathered intensitymeasurements 300 for the highway 150 shown in FIG. 11. The intensitymeasurements 300, along with the sign 190 location and sign 190 colors,were used to create R_(A) values for the discrete locations within thelane of travel. A “point cloud” of data points was then calculated tocreate a full three-dimensional sign R_(A) profile 590 for thisparticular sign 190 along the entire highway 150.

FIG. 12 shows a three-dimensional representation of the point cloud ofR_(A) values for the sign 190 along the highway 150. The height of thethree-dimensional sign profile 590 at each point represents that sign's190 R_(A) value at that point. Planning and maintenance departmentswithin transportation agencies will see the obvious benefits ingraphically representing a sign's 190 R_(A) performance over the surfaceof a highway 150. Along with understanding a sign's 190 currentperformance, these agencies can use the R_(A) profile software tounderstand how changes to a sign 190 can affect its performance along agiven highway 150.

FIG. 13 shows the impact of one possible variable on the sign's 190three-dimensional sign R_(A) profile 590. If, for example, the measuredsign 190 utilized a medium performance sheeting type, the displaysoftware can show the impact of changing the sheeting type for this sign190. The display software has performance curves for the desiredsheeting type and computes the new three-dimensional sign R_(A) profile590 for this sign 190 using its current location, size, and facingdirection.

FIG. 14 shows how changing the sign 190 angle (which changes theentrance angle 160) would impact the sign's 190 three-dimensional signR_(A) profile 590. Even though a system fabricated, according to thepresent invention, may not have direct measurement or other dataregarding the exact angle entrance angle 160, one may use the computedR_(A) data points to create a three-dimensional sign R_(A) profile 590and rotate the three-dimensional sign R_(A) profile 590 as specified bythe user any arbitrary degree or fraction thereof. This feature assiststraffic sign maintenance department personnel in “tuning R_(A) to thehighway 150” for all or any portion of such object's of interest 460and/or each roadside sign 190 (i.e., various entrance angles 160 fromdifferent segments of a vehicle pathway yield different results).

If a sign 190 on the right hand side of the road is rotated on an axisperpendicular to a vehicle pathway one may not have enough computedR_(A) points from the capture vehicle 225 given the track or path ofsuch vehicle with which to compute the complete three-dimensional signR_(A) profile 590 for the entire highway 150 surface. However, if weknow the normal vector 180 for the sign 190 (via any of the variousmethods described herein), one may use the typical horizontal symmetryof sign 190 sheeting materials to create the rest of thethree-dimensional sign R_(A) profile 590.

As mentioned earlier, observation angle 100 is a key determinant forsign 190 R_(A) behavior. The light intensity measurement system 230contained herein attempts to eliminate this variable by placing the highoutput light source(s) 270 and light intensity sensor 280 very close toone another. Planning departments can change observation angles 100within the three-dimensional sign R_(A) profile 590 software tounderstand its impact on sign 190 performance. Since thethree-dimensional sign R_(A) profile 590 software knows the as-measuredsign 190 sheeting type and has available an R_(A) performance profile(preferably embedded in a look up table of all popular or requiredsheeting types and/or as stored in memory, or dynamically generated foruse in practicing the present invention), a new three-dimensional signR_(A) profile 590 can be generated for the newly-desired observationangle 100. FIG. 15 shows the observation angle simulation 620 for thesign 190 along the sample highway 150 when the observation angle 100 ischanged from its present value to a higher value.

The aforementioned three-dimensional sign R_(A) profile 590 is one wayof utilizing the R_(A) data to assess the object's of interest 460performance. A “virtual drive-through” is another method of utilizingthe computed R_(A) data. Virtual drive-throughs are a popular tool usedby transportation and planning departments. These drive-throughs consistof creating a three-dimensional volumetric model of a particular highway150. Users of virtual drive-through applications can then move the viewpoint along the highway 150 to understand what a driver (in a passengervehicle, for example) would see as they traversed the selected highway150. These drive-throughs, however, are usually modeled usinginformation from the daytime scene.

Nighttime drive-throughs, on the other hand, can provide usefulinformation beyond what can be learned from daytime drive-throughs. Toproperly represent nighttime drive-throughs, accurate information mustbe integrated regarding the nighttime performance of the objects ofinterest 460. As a result of the creation of an three-dimensional signR_(A) profile 590 for each object of interest 460, these objects ofinterest 460 assets can be placed in the virtual drive-through at theirprecise locations along the highway 150 (or on the highway 150 in thecase of pavement markings 630). Utilizing nighttime asset performance ina virtual drive-through can highlight design or implementation problemsthat are not apparent with daytime virtual drive-throughs. Assessment ofnighttime accidents can be significantly enhanced by using nighttimeasset performance information in virtual drive-throughs.

Although the use of the three-dimensional sign R_(A) profile 590 hasbeen described with respect to R_(A) values as determined by measurementof light intensity, it will be understood that the software formanipulating the three-dimensional sign R_(A) profile 590 and thevirtual drive-through can work equally as well in other modes whereknown data values are provided for some or all of the to R_(A) values.For example, planning departments could insert R_(A) values for knownsheeting types of planned signs along a roadway in order to conduct anight time virtual drive through utilizing the software in accordancewith the present invention to manipulate the location and placement ofsuch signs to achieve better visibility.

Reflective pavement markings 630 display similar properties to objectsof interest 460 (and other reflective objects), but the determination ofpavement marking 630 retroreflectivity requires some extra constraints.Pavement marking 630 retroreflectivity is expressed in millicandelas persquare meter per lux (mcd/m²/lux) and is designated R_(L). Along withobservation angle 100 and entrance angle 160, the lateral distance 220between the light source 110 and the pavement markings 630 must also beknown. FIG. 16 shows the R_(L) geometry for a typical passenger vehicle140.

Studies have shown that there is no correlation between pavement marking630 retroreflectivity (R_(L)) values with different geometries. Becauseof this lack of correlation, agreed-upon geometries must be utilizedwhen measuring intensity and reporting R_(L). When measuring intensityand computing R_(A) the present invention attempts to dramaticallyreduce (essentially eliminate) observation angle 100 with the highoutput light source 270 and light intensity sensor 280 placement. Whenmeasuring intensity for computing R_(L), it is preferable to positionthe high output light source 270 and the light intensity sensor 280 suchthat the agreed-upon geometry is met for the desired measurementdistance. At the time of this disclosure, both the European Committeefor Normalization and the American Society for Testing and Materials(ASTM) have standardized on the same R_(L) geometry of 1.05 degreeobservation angle 100, 88.76 degree entrance angle 160, and 30 metermeasurement distance 220.

The intensity of light reflected from pavement markings 630 will be lessthan that of signs 190. As a result, another light intensity sensor 280may be needed for the determination of R_(L). Therefore, there are tworeasons for requiring a different light intensity sensor 280 fordetermining R_(A) and R_(L)—the range of intensities and the placementof the light intensity sensor 280. However, the same high output lightsource(s) 270 can be used for determining R_(A) and R_(L).

The present invention has been described with respect to particularillustrative embodiments. It is to be understood that the invention isnot limited to the above-described embodiments and modificationsthereto, and that various changes and modifications may be made by thoseof ordinary skill in the art without departing from the spirit and scopeof the appended claims.

1. A method for displaying and manipulating retroreflectivity data for areflective surface disposed along a roadway comprising: determining aplurality of retroreflectivity values for the reflective surface;generating a three-dimensional representation of retroreflectivityvalues of the reflective surface; and displaying the three-dimensionalrepresentation of retroreflectivity values.
 2. A method of automateddetermination of retroreflectivity values for reflective surfacescomprising: strobing a light source to illuminate an area that includesat least one reflective surface without targeting the light source on aparticular reflective surface; collecting a plurality of light intensitymeasurements with at least one intensity sensor directed to cover afield of view which includes at least a portion of the area illuminatedby the light source; and using a computer processing system to: identifya portion of at least one light intensity measurement associated withone of the at least one reflective surfaces; and analyze the portion ofthe at least one light intensity measurement to determine at least oneretroreflectivity value for that reflective surface.
 3. A method ofautomated determination of retroreflectivity values for reflectivesurfaces disposed along a roadway comprising: strobing a light source asthe light source is traversed along the roadway to illuminate an areathat includes at least one reflective surface; collecting a plurality oflight intensity measurements with at least one intensity sensor directedto cover a field of view which includes at least a portion of the areailluminated by the light source; and using a computer processing systemto: identify a portion of at least one light intensity measurementassociated with one of the at least one reflective surfaces; and analyzethe portion of the at least one light intensity measurement to determineat least one retroreflectivity value for that reflective surface.